Cognitive R&D – Leveraging Cognitive Search and Analytics to Amplify Research and Development Expertise

Forces of global competition, narrow margins, higher product development costs, and tenuous exclusivity holds drive organizations to push innovation, seek cost cutting strategies, and go-to-market as quickly as possible. Demands change frequently while regulatory and compliance standards become even more stringent. Organizations must keep up, and the pressure on research and development (R&D) never stops. R&D is the critical driver within the organization, whether within a large aircraft manufacturer or a leading automobile company looking to develop cutting edge products and services or a pharmaceutical company accelerating time-to-market for new drugs or a CPG company reinventing waning products. R&D thrives on information: customer information, expert information, product information, scientific information, market information, and competitive information.

To be at the forefront of innovation, R&D departments need complete visibility into both new and historical information across the entire enterprise as well as access to research from external public and premium information services. This is no simple task in today’s world where we are inundated with data — more data, more opportunities and more challenges. As a result, many companies depend on Cognitive Search and Analytics (CS&A) solutions to harness insightful, high-quality information and fuel innovation within their product and solution portfolios.

THE PRESSURE ON R&D

As organizations strive to create value, enhance customer experiences, and differentiate themselves from their competition, they have placed demands on their R&D departments to:

  • Accelerate delivery of innovative products to market
  • Optimize and manage available resources and knowledge while leveraging intellectual property
  • Devise methods to reduce product development costs and eliminate re-work
  • Improve product compliance both internally and externally and deliver safer, compliant products faster
  • Understand consumer and market demands and improve responsiveness
  • Resolve product issues quickly and efficiently to gain and keep customer trust

To meet these demands, R&D depends on complex scientific and engineering content that contains implicit conceptual relationships that can and should be semantically linked to simplify access to the knowledge embedded in that content.

HOW COGNITIVE SEARCH AND ANALYTICS HELPS

Cognitive Search and Analytics solutions amplify the expertise of R&D departments by surfacing insights from data across the enterprise, irrespective of location and format. From a single, secure access point, these solutions enable R&D professionals to unlock relevant and timely product research that helps make informed decisions. In addition, these capabilities are not limited to internal information; users can quickly access information from external Web sites and other applications, deriving relevant information and seamlessly integrating with internal enterprise information.

Cognitive Search and Analytics solutions enable enterprises to maximize the value of their intellectual property. Powerful search relevance and navigation capabilities enable researchers to find valuable pieces of past research and even parallel work going on without each group knowing about the other — eliminating duplicate work, reducing time spent in trials and shortening development cycles. These solutions allow employees to tag, bookmark and comment on documents, enabling collaboration and making teams more innovative, efficient and productive. Surfacing this existing knowledge enables workers to leverage the past work of distant or former researchers to benefit future research. Dynamically delivering relevant information, surfacing knowledge and enabling collaboration can decrease R&D costs significantly. Because R&D departments need to comply with a myriad of complex regulations, they need to be aware of relevant regulations without having to sift through the myriads themselves. This visibility enables R&D to stay abreast of regulatory mandates and efficiently manage compliance. Organizations can also leverage these solutions to send alerts to employees when there are new policy and compliance changes so that relevant R&D stakeholders are immediately notified.

Managing and maintaining product specifications is a critical function within R&D. Cognitive Search and Analytics solutions can access virtually any data source and expose changes when information is deleted or becomes outdated. These solutions can alert workers when any new information is created that impacts their specific process in the development cycle. These solutions also track and respect the access permissions accorded by each target application; only those with the correct privileges can access restricted information. Cognitive Search & Analytics solutions give researchers clear insight into product requirements and enable them to collaboratively develop safer, higher quality products that meet regulatory requirements.

RAPID RETRIEVAL OF RELEVANT INFORMATION MAKES THE DIFFERENCE

Extracting relevant information from vast and complex data volumes is a challenge that requires a sophisticated and scalable solution. The Sinequa Cognitive Search and Analytics platform handles all structured and unstructured data sources and uses Natural Language Processing (NLP), statistical analysis and Machine Learning (ML) to create an enriched “Logical Data Warehouse” (LDW). You can think of it as a repository of information about data and about relationships between data, people, concepts, etc. This LDW is optimized for performance in delivering rapid responses to users’ information needs. Users can ask questions in their native language or ask that relevant information be “pushed” to them in a timely fashion when it emerges. More than 150 connectors ready for use “out of the box” make the process of connecting multiple data sources fast and seamless. Company and industry-specific dictionaries and ontologies can be easily integrated, putting domain-specific knowledge “under the hood” of the Sinequa platform, making it an intelligent partner for anyone in search of relevant information.

With Sinequa, researchers, designers and engineers have immediate access to all the information needed to work productively.

With Sinequa, researchers, designers and engineers have immediate access to all the information needed to work productively.

The advanced semantic capabilities within Sinequa’s platform provide strong relevance in 21 different languages to assist organizations with even the most geographically and linguistically diverse workforce.

REAL-WORLD EXAMPLE: AMPLIFYING BIOPHARMA EXPERTISE

Consider one of Sinequa’s biopharma customers, a research-intensive organization dealing with a vast number of highly technical documents, produced both in-house and externally. The information in these documents varies according to the field of its origin – e.g. medical, pharmaceutical, biological, chemical, biochemical, genetic, etc. – and may deal with diseases, genes, drugs/active agents, and mechanisms of action. A lot of the information is textual, but there is also structured information, like molecular structures, formulae, curves, diagrams, etc. The volume of this information is on the order of magnitude of about 500 million documents and billions of database records.

Now consider the more than 10,000 R&D experts within the organization trying to leverage this information daily. They need to be able to ask topical questions, find relevant people and documents, and explore the vast information landscape to discover knowledge. The Sinequa platform supports this by plowing through the hundreds of millions of documents and equally large amounts of structured data, analyzing the data, analyzing the natural language user queries, and classifying results by category in real time. With the data tamed and enriched, it is presented to the user via a simple, intuitive interface with faceted navigation aids that allow the user to filter results further based on structural attributes that are either explicit or were intelligently derived by the system. The interfaces, also referred to as search-based applications (SBAs) are configured to expose functionality that is very specific to an R&D expert, aligning the solution with the goals of the user.

The Sinequa solution has proven to be very valuable to the customer in question, putting both internal and external research–related information that scientists need for research, development, and decision making into a single virtual repository with advanced navigation and retrieval capabilities. It has also proved to be very beneficial to teams of research and development contributors by allowing experts around the world to collaborate more easily through a single research application. Features such as navigation by topic across multiple repositories, de-duplication of similar documents, and improved research capabilities have all made knowledge workers more efficient and innovative.

CONCLUSION

Sinequa’s Cognitive Search & Analytics platform leverages relevant customer and market information to give R&D organizations insight and the ability to react quickly to demands. Teams utilize this platform to collaborate and share information. Sinequa effectively eliminates data silos and delivers relevant information from data to users in their business context, such that they can make better decisions, drive innovation, reduce risk, and be more efficient, which in turn enables forward-thinking R&D departments that thrive on continuous product improvements and introductions to amplify the collective expertise of the organization.

+1Share on LinkedInShare on Twitter

The Heat in The Trend Point: April 22 to April 26

Enterprise search does not always get the attention it deserves but recently we have seen a crop of articles on this vital technology in The Trend Point.

An efficient and agile user experience is an incredibly sought after characteristic in enterprise search today. The article cited in “Usability of Enterprise Search Valued” shares the following opinion:

There are too many IT consoles, too many vendors — one for network management, one for help desk, one for application performance,” said Raj Sabhlok, president of ManageEngine’s parent company Zoho. Pity the poor admins who have to piece all that information together to figure out what’s going on, or worse, what went wrong. The search function promises these woebegone admins a “Google-like interface” that lets them search on a device name, for example, and get back every instance in which that name crops up.

This has in fact more to do with the search function than with a search interface: Enterprise Search is good at pulling together all relevant information on a given topic, providing the notorious 360° view. In the long run, systems administrators will not want to have a “Google-like” interface to see the 360° view of the problem domain they are working on. They will probably want a mix of dashboards, facets and lists ordered by relevance. Such interfaces will be part of Search Based Applications on top of a Unified Information Access platform (aka as Enterprise Search platform).

A strategic disconnect between IT and business leaders can often drive IT professionals to have to build the case for innovative enterprise search software. In, “Podcast Offers Tips on Building Business Case for Enterprise Search” the following recommendations were given:

*The first steps to take to show business leaders the real value that enterprise search has to offer and convince them it’s time to implement a search program;

*Key questions that project managers and business stakeholders within an organization should ask of themselves when developing a formal enterprise search technology business strategy;

*The change management aspect of putting an enterprise search program in place;

*Liewehr’s take on how to build an enterprise search team and who should be in charge of shepherding the project;

*How enterprise search technology can be used to support; and

*Best practices on how to develop an enterprise search technology review process to ensure adoption and implementation success.

Enterprise organizations of all shapes have a need for enterprise search and while none of the articles referenced here pointed to the innovative aspects of current search technologies that does not mean there are no companies enjoying an advantage because of them. The fact that there are still many mentions purely in regards to enterprise search shows that the core technology is absolutely essential. Of course, semantic capabilities and the spread across structured and unstructured data that Unified Information Access offers are the type of search technologies that will be brining home stronger ROI and the implication of business stakeholders.

Jane Smith, May 1, 2013

Sponsored by ArnoldIT.com, developer of Beyond Search

+1Share on LinkedInShare on Twitter

The Heat in The Trend Point: April 15 to April 19

In The Trend Point, we have seen visualization and end user output presentation become a topic of prevalence recently.

Some sources report that visualization tools are still in the early phases of evolution. According to the article referenced in “From Raw Data to Informed Visualization“:

I would say that it is all very contingent. As we know, there are good visuals and there are bad visuals, and we’ve all seen a lot of bad visuals in PowerPoint, for example. Edward Tufte has made a pretty good living demonstrating there are really bad approaches to visuals that often occur in PowerPoints. I think we are probably a lot farther along in the world of narrative — we’ve been doing that for thousands of years — than we are in visual displays of information. I think we are really just finding our way now.

One article, “Data and Graphics Matched Through Search and Visualization,” suggested that not all data needs to be visualized, Jim Stikeleather of the Havard Business Review shares that in the end, the concept of translating the minutia of data points into something that is both interpretable and relevant is most important:

Ultimately, data visualization is about communicating an idea that will drive action. Understanding the criteria for information to provide valuable insights and the reasoning behind constructing data visualizations will help you do that with efficiency and impact.

Another article posits that visualization is the natural best method to present data. The source pointed to in “Visualization Must Be Included in Search and Analytics” tells us:

 One of the best ways to get your message across is to use a visualization to quickly draw attention to the key messages, and by presenting data visually it’s also possible to uncover surprising patterns and observations that wouldn’t be apparent from looking at stats alone … By visualizing information, we turn it into a landscape that you can explore with your eyes, a sort of information map. And when you’re lost in information, an information map is kind of useful.

Is data visualization not the same as simply developing and idea and sharing it in an accessible way? A new name for the basics of creating and presenting information is fine. However, as far as Sinequa‘s technology goes, it provides a much easier and more intuitive user experience for delivering real time and agile information and insights to users. It does not deliver the one picture that will hit you between the eyes and make you act near-automatically (why would we need a human to provide that reaction?). The interaction paradigm is that of “ping-pong between human and search engine. There is no need to involve complex business intelligence codes. Innovative enterprise search is the core that facilitates this kind of representation through a graphical interface.

Jane Smith, April 24, 2012

Sponsored by ArnoldIT.com, developer of Augmentext.

+1Share on LinkedInShare on Twitter